Nowadays, different models [1]}, [2]} have tackled these problems and advancing solutions to the problem of the low resolution on the output maps.
For better refinement, previous models [3]} post-process the results to enhance them, e.g., Conditional Random Fields (CRF) [4]}.
For global feature extraction with more information, new architectures [5]}, [6]}, [7]} were created as well as sparse convolution operations [8]}, [9]}.
Commonly, methods in SS use hourglass models [10]}, [11]}, [12]} that comprise a coding and decoding stages to recover the pixel-wise position of the segmented objects.
